Portfolio optimization: with using a hybrid evolutionary recursive discrete imperialist competitive algorithm and genetic algorithm RD-ICGA (case study TSE)

AB STRACT In this research toward optimizing resource allocation, an innovative learning algorithm will used to select and optimize portfolio in Tehran Stock Exchange .A new method was proposed based on the combination of ICA (Imperial Competitive Algorithm) and GA (Genetic Algorithm) which improves the convergence speed and accuracy of the optimization results.. The obtained results show that compared with the previous method, the proposed algorithms are at least 32% faster in optimization processes; also the variance convergence speed is smaller than the ICA and GA.